INTEGRATING DATA ANALYSIS INTO COURSE CONTENT

The acquisition of analytical skills is broadly acknowledged to be a central component of a university education. In most college curricula, general education courses emphasize the development of verbal analysis and writing skills. Less attention has been given to the development of fundamental skills in the analysis of quantitative data. In introductory biology courses at North Park University, we have consciously incorporated a multi-step introduction to the use of graphing and statistics in the analysis of data collected in the laboratory.

During the last few years both of the authors have developed programs to implement decision making activities and graphing into our courses. Well chosen and well constructed graphs are important tools for the analysis and display of data. The advent of computer graphing tools has made it possible to construct a wide variety of graphs. These types of assignments help undergraduates, who have little experience in selecting and preparing meaningful graphs, integrate the content skills with their practical applications..

Biology laboratories offer a context for the development of the fundamentals in the use of graphs for data analysis and presentation. We use the framework of various courses to be the entry for developing the skills described. Linking specific aspects of data analysis to the processing of data collected in the laboratory underscores the practical applications of graphing and statistical analysis. The ability to complete analysis of laboratory data raises the laboratory experience from a routine exercise to a more meaningful and unified demonstration of a concept. Trend lines, regression analysis, use of scale, multiple axes, selection of proper graphing styles, and hypothesis testing are part of student assignments.

Students use a variety of techniques as they investigate the relationship between modeling and statistics. For example, students
• use spreadsheets to pose and model “what if?” questions related to populations and the environment.
• explore ways that statistics is used in a variety of situations such as clinical trials
• use the Internet to find large data sets to use in sampling and hypothesis testing investigations.
• use computer software to analyze data
• use computer software and special plotter printers to present their findings both in oral and visual presentations and in poster presentations.

Both authors will show examples of the assignments and work from their students using PowerPoint. For those who would like to know more about these projects, further information will be available on a web site.